DialogRE^C+: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs

Dialogue relation extraction (DRE) that identifies the relations between argument pairs in dialogue text, suffers much from the frequent occurrence of personal pronouns, or entity and speaker coreference. This work introduces a new benchmark dataset DialogRE^C+, introducing coreference resolution into the DRE scenario. With the aid of high-quality coreference knowledge, the reasoning of argument relations is expected to be enhanced. In DialogRE^C+ dataset, we manually annotate total 5,068 coreference chains over 36,369 argument mentions based on the existing DialogRE data, where four different coreference chain types namely speaker chain, person chain, location chain and organization chain are explicitly marked. We further develop 4 coreference-enhanced graph-based DRE models, which learn effective coreference representations for improving the DRE task. We also train a coreference resolution model based on our annotations and evaluate the effect of automatically extracted coreference chains demonstrating the practicality of our dataset and its potential to other domains and tasks.Comment: Accepted by NLPCC 202

Data-Layout Optimization Using Reuse Distance Distribution

Abstract. As the ever-increasing gap between the speed of processor and the speed of memory has become the cause of one of primary bottlenecks of computer systems, modern architecture systems use cache to solve this problem, whose utility heavily depends on program data locality. This paper introduces a platform independent data-layout optimization framework to improve program data locality. This framework uses a variable relation model based on variables' reuse distance distribution to quantitate the relation of variables and accordingly assigns variables which are often accessed together in one group. At the same time this framework introduces a dynamic array regrouping method to group dynamic arrays assigned in a group. Experiments show that this data-layout optimization framework can effectively improve program data locality and program performance

Optical characterization of Chinese hybrid rice using laser-induced fluorescence techniques—laboratory and remote-sensing measurements

Chinese hybrid rice of different varieties, growing in paddies in the Pingqiao district, north of Xinyang city, Henan province, China, was studied in detailed spectroscopic characteristics using laser-induced fluorescence. The base for the studies was the new South China Normal University mobile lidar laboratory, which was dispatched on site, providing facilities both for laboratory studies using a 405 nm excitation source as well as remote sensing measurements at ranges from around 40 m–120 m, mostly employing the 532 nm output from a Nd:YAG laser. We, in particular, studied the spectral influence of the species varieties as well as the level of nitrogen fertilization supplied. Specially developed contrast functions as well as multivariate techniques with principal components and Fisher’s discriminate analyses were applied, and useful characterization of the rice could be achieved. The chlorophyll content mapping of the 30 zones was obtained with the remote sensing measurements

NTIRE 2019 Challenge on Real Image Denoising: Methods and Results

This paper reviews the NTIRE 2019 challenge on real image denoising with focus on the proposed methods and their results. The challenge has two tracks for quantitatively evaluating image denoising performance in (1) the Bayer- pattern raw-RGB and (2) the standard RGB (sRGB) color spaces. The tracks had 216 and 220 registered participants, respectively. A total of 15 teams, proposing 17 methods, competed in the final phase of the challenge. The proposed methods by the 15 teams represent the current state-of-the- art performance in image denoising targeting real noisy im- ages